Androgen deficiency in the adult male

Introduction. The purpose of this study was to investigate the association between severity of lower urinary tract symptoms (LUTS), erectile dysfunction (ED) and metabolic syndrome.

Methods. Our study population included a consecutive series of 190 patients with LUTS (International Prostate Symptom Score-IPSS >7) with or without manifestations of the metabolic syndrome. The diagnoses of diabetes mellitus and hypertension were obtained from the patient's medical history. Data on blood pressure, waist measure, body height and weight were collected and body mass index were calculated. Patients were assessed based on the International Index of Erectile Function (IIEF) for ED and IPSS and IPSS-Quality of Life for LUTS. Blood samples were drawn from fasting patients to determine, fasting blood glucose (FBG), triglycerides, HDL-cholesterol and serum total testosterone levels.

Results. In severe LUTS patient group, IIEF erectile function domain scores were significantly lower than moderate LUTS patient group (p < 0.05). Multiple logistic regression analysis confirmed that presence of ED was the most predictor of severe LUTS. The prevalence of metabolic syndrome was higher in patients with severe LUTS (26%vs. 46%, p = 0.009). The severe form of the LUTS was significantly correlated with waist circumference >102 cm (p < 0.05), blood pressure ≥130/85 mmHg (p < 0.05) and FBG >110 mg/dl (p < 0.01).

Conclusion. Obesity, high plasma level of FBG and hypertension constitute risk factors for the development of severe LUTS. Metabolic syndrome may play a key role in the pathogenesis in both ED and LUTS. Presence of ED is the most predictor of severe LUTS.     

Constructing a social space for Alevi political identity: religion,antagonism and collective passion

ABSTRACT

This paper analyses the construction of an Alevi political identity in terms of cultural, social and religious values at a time when the role of religion is increasing in the political life of Turkey. It indicates the emergence of a new form of conflict and hegemonic articulation between Sunnism and Alevism that offers an alternative means of conflict resolution by the Alevi political agents within a radical pluralism and agonistic democracy. It also argues that the social construction of Alevi political identity is both a political project and an ontological question as this identity focuses on religious discourses in establishing a counter-hegemonic culture through mobilizing political ‘collective passion’.     

Rank-based ridge estimation in multiple linear regression

Multicollinearity and model misspecification are frequently encountered problems in practice that produce undesirable effects on classical ordinary least squares (OLS) regression estimator. The ridge regression estimator is an important tool to reduce the effects of multicollinearity, but it is still sensitive to a model misspecification of error distribution. Although rank-based statistical inference has desirable robustness properties compared to the OLS procedures, it can be unstable in the presence of multicollinearity. This paper introduces a rank regression estimator for regression parameters and develops tests for general linear hypotheses in a multiple linear regression model. The proposed estimator and the tests have desirable robustness features against the multicollinearity and model misspecification of error distribution. Asymptotic behaviours of the proposed estimator and the test statistics are investigated. Real and simulated data sets are used to demonstrate the feasibility and the performance of the estimator and the tests.     

Parametric estimation of location and scale parameters in ranked set sampling

This paper develops parametric inference for the parameters of location-scale family of distributions based on a ranked set sample. Likelihood function incorporates within-set ranking errors into the model through a missing data mechanism. The maximum likelihood estimators of the location-scale and missing data model parameters are constructed and an EM-algorithm is provided. It is shown that the proposed estimator is robust against imperfect ranking error and provides higher efficiency over its competitors.     

Ratio estimators based on a ranked set sample in a finite population setting

This paper considers the ratio estimator in a finite population setting in a ranked set sampling (RSS) design, where the sample is constructed either with or without replacement policies. It is shown that the proposed ratio estimator is slightly biased, but the amount of bias is smaller than the amount of bias of a simple random sample (SRS) ratio estimator. For the proposed ratio estimator, the paper provides explicit expressions for its mean square error and precision relative to the other competing estimators. It is shown that the new estimator has a substantial amount of improvement in efficiency with respect to SRS estimator. The proposed estimator is applied to two different finite population settings to estimate population mean.     

Nonviolent resistance: a treatment for parents of children with acute behavior problems

Nonviolent resistance (NVR) is a new training model aimed at helping parents deal effectively with their helplessness, isolation, and escalatory interactions with their children. The purpose of this study is to evaluate training in NVR with the parents of children with acute behavior problems. Seventy-three parents (41 families) were randomly assigned to a treatment group and wait-list control group. Measures were taken at pretreatment, posttreatment, and a 1-month follow-up. In comparison with the wait-list group, parents who received training in NVR showed a decrease in parental helplessness and escalatory behaviors, and an increase in perceived social support. The children's negative behaviors as assessed by the parents also decreased significantly.     

Quantile inference based on partially rank-ordered set samples

This paper develops statistical inference for population quantiles based on a partially rank-ordered set (PROS) sample design. A PROS sample design is similar to a ranked set sample with some clear differences. This design first creates partially rank-ordered subsets by allowing ties whenever the units in a set cannot be ranked with high confidence. It then selects a unit for full measurement at random from one of these partially rank-ordered subsets. The paper develops a point estimator, confidence interval and hypothesis testing procedure for the population quantile of order p. Exact, as well as asymptotic, distribution of the test statistic is derived. It is shown that the null distribution of the test statistic is distribution-free, and statistical inference is reasonably robust against possible ranking errors in ranking process.     

Turkey's Response to Sex Trafficking of Migrant Women: Is It Efficient Enough?

Human trafficking for sexual exploitation is a serious problem affecting especially women and children. Turkey has been particularly affected by sex trafficking because of the large numbers of female migrants that it receives. This article aims to critically assess the effectiveness of Turkey's current policies against sex trafficking using a feminist theoretical perspective with a particular focus on migrant women. To this end, the scope of the problem in Turkey, the supply and demand sides of sex trafficking, and the existing policies are discussed. Sex trafficking is examined at the intersection of Turkey's migration and prostitution regimes. It is argued that Turkey's response to sex trafficking has been inefficient because it currently focuses only on the economic supply side of the problem, ignoring the patriarchal demand side of it. The article concludes with a discussion of policy recommendations for Turkey that could help reduce sex trafficking in this country.     

Mixture Model Analysis of Partially Rank‐Ordered Set Samples: Age Groups of Fish from Length‐Frequency Data

We present a novel methodology for estimating the parameters of a finite mixture model (FMM) based on partially rank‐ordered set (PROS) sampling and use it in a fishery application. A PROS sampling design first selects a simple random sample of fish and creates partially rank‐ordered judgement subsets by dividing units into subsets of prespecified sizes. The final measurements are then obtained from these partially ordered judgement subsets. The traditional expectation–maximization algorithm is not directly applicable for these observations. We propose a suitable expectation–maximization algorithm to estimate the parameters of the FMMs based on PROS samples. We also study the problem of classification of the PROS sample into the components of the FMM. We show that the maximum likelihood estimators based on PROS samples perform substantially better than their simple random sample counterparts even with small samples. The results are used to classify a fish population using the length‐frequency data.     

Complete characterization of functions satisfying the conditions of Arrow’s theorem

Arrow??s theorem implies that a social welfare function satisfying Transitivity, the Weak Pareto Principle (Unanimity), and Independence of Irrelevant Alternatives (IIA) must be dictatorial. When non-strict preferences are also allowed, a dictatorial social welfare function is defined as a function for which there exists a single voter whose strict preferences are followed. This definition allows for many different dictatorial functions, since non-strict preferences of the dictator are not necessarily followed. In particular, we construct examples of dictatorial functions which do not satisfy Transitivity and IIA. Thus Arrow??s theorem, in the case of non-strict preferences, does not provide a complete characterization of all social welfare functions satisfying Transitivity, the Weak Pareto Principle, and IIA. The main results of this article provide such a characterization for Arrow??s theorem, as well as for follow up results by Wilson. In particular, we strengthen Arrow??s and Wilson??s result by giving an exact if and only if condition for a function to satisfy Transitivity and IIA (and the Weak Pareto Principle). Additionally, we derive formulae for the number of functions satisfying these conditions.